Zobrazeno 1 - 10
of 716
pro vyhledávání: '"Anees-ur Rehman"'
Autor:
Qazi, Mohammad Areeb, Hashmi, Anees Ur Rehman, Sanjeev, Santosh, Almakky, Ibrahim, Saeed, Numan, Gonzalez, Camila, Yaqub, Mohammad
Deep Learning has shown great success in reshaping medical imaging, yet it faces numerous challenges hindering widespread application. Issues like catastrophic forgetting and distribution shifts in the continuously evolving data stream increase the g
Externí odkaz:
http://arxiv.org/abs/2405.13482
Brain tumor segmentation is a fundamental step in assessing a patient's cancer progression. However, manual segmentation demands significant expert time to identify tumors in 3D multimodal brain MRI scans accurately. This reliance on manual segmentat
Externí odkaz:
http://arxiv.org/abs/2405.02852
Autor:
Qazi, Mohammad Areeb, Almakky, Ibrahim, Hashmi, Anees Ur Rehman, Sanjeev, Santosh, Yaqub, Mohammad
Continual learning, the ability to acquire knowledge from new data while retaining previously learned information, is a fundamental challenge in machine learning. Various approaches, including memory replay, knowledge distillation, model regularizati
Externí odkaz:
http://arxiv.org/abs/2404.14099
Explaining Deep Learning models is becoming increasingly important in the face of daily emerging multimodal models, particularly in safety-critical domains like medical imaging. However, the lack of detailed investigations into the performance of exp
Externí odkaz:
http://arxiv.org/abs/2403.18996
Autor:
Sanjeev, Santosh, Zhaksylyk, Nuren, Almakky, Ibrahim, Hashmi, Anees Ur Rehman, Qazi, Mohammad Areeb, Yaqub, Mohammad
The scarcity of well-annotated medical datasets requires leveraging transfer learning from broader datasets like ImageNet or pre-trained models like CLIP. Model soups averages multiple fine-tuned models aiming to improve performance on In-Domain (ID)
Externí odkaz:
http://arxiv.org/abs/2403.13341
Autor:
Almakky, Ibrahim, Sanjeev, Santosh, Hashmi, Anees Ur Rehman, Qazi, Mohammad Areeb, Yaqub, Mohammad
Transfer learning has become a powerful tool to initialize deep learning models to achieve faster convergence and higher performance. This is especially useful in the medical imaging analysis domain, where data scarcity limits possible performance ga
Externí odkaz:
http://arxiv.org/abs/2403.11646
Autor:
Maani, Fadillah, Hashmi, Anees Ur Rehman, Aljuboory, Mariam, Saeed, Numan, Sobirov, Ikboljon, Yaqub, Mohammad
Automated segmentation proves to be a valuable tool in precisely detecting tumors within medical images. The accurate identification and segmentation of tumor types hold paramount importance in diagnosing, monitoring, and treating highly fatal brain
Externí odkaz:
http://arxiv.org/abs/2403.09262
Autor:
Hashmi, Anees Ur Rehman, Almakky, Ibrahim, Qazi, Mohammad Areeb, Sanjeev, Santosh, Papineni, Vijay Ram, Jagdish, Jagalpathy, Yaqub, Mohammad
Large-scale generative models have demonstrated impressive capabilities in producing visually compelling images, with increasing applications in medical imaging. However, they continue to grapple with hallucination challenges and the generation of an
Externí odkaz:
http://arxiv.org/abs/2403.09240
Autor:
Saba Rasheed, Anees ur Rehman, Zermina Tasleem, Marryam Azeem, Muhammad Fawad Rasool, Arifa Mehreen, Saleh Karamah Al-Tamimi
Publikováno v:
Journal of Patient-Reported Outcomes, Vol 8, Iss 1, Pp 1-15 (2024)
Abstract Background Psychological Insulin Resistance (PIR) and negative perceptions regarding insulin treatment are noteworthy challenges in T2DM management, which hinder the timely initiation of insulin treatment. To get past these obstacles a relia
Externí odkaz:
https://doaj.org/article/f0a741caa9084301a6a04ab00a7cc9cf
Autor:
Memoona Nisar, Zermina Tasleem, Sohail Ayaz Muhammad, Asma Javid, Muhammad Fawad Rasool, Hidayah Karuniawati, Saleh Karamah Al-Tamimi, Anees Ur Rehman
Publikováno v:
Cost Effectiveness and Resource Allocation, Vol 22, Iss 1, Pp 1-14 (2024)
Abstract Background The direct and indirect costs of chronic kidney disease (CKD) are substantial and increase over time. Concerns regarding our capacity to manage the financial burden that CKD) places on patients, caregivers, and society are raised
Externí odkaz:
https://doaj.org/article/056ab0bb1b244a02a64199a1ee949a72